Method and system for memory allocation in a disaggregated memory architecture

ABSTRACT

Embodiments of the present invention disclose a method, computer program product, and system for allocating memory. A computer receives a request for memory to be allocated to a computer node and determines if the allocation request needs to be carried out on a cluster level, a server rack level, or on a server level. The computer retrieves a memory policy associated with the determined level the allocation request needs to be carried out on from a memory policy database and determines how much available memory may be allocated and if there enough available memory to meet the request. The computer reallocates the available memory to address the received the received request based on the retrieved memory policy.

BACKGROUND

The present invention relates generally to the field of computer memory,and more particularly to allocation of memory in a server level, rack,and/or cluster farm.

Today it is common to run a big workload with hundreds of servers as acluster. When a particular workload consumes almost all the memory, thesystem cannot leverage the remaining computing power on that serveralthough the CPU utilization is still low. The typical approach to solvethis problem is to transform the workload into a scale-out design sothat the small workload can be dispatched to other servers in thiscluster. However, there are still two problems this approach. First, ifthis workload is a memory-intensive workload that cannot be transformedinto a scale-out architecture, this will become a hot-spot in the systemperformance. Although other servers may have a lot of free memory duringnon-peak or even idle time, such memory cannot be shared. Second, eventhough small-granularity workload can be distributed to other serversvia delicate software architecture design, this will rely on a clusterscheduler to perform this task. It means the transfer of workloadstate/data across the nodes. In a big data scenario, this violates the“move computing close to data” principle. In both scenarios, these willlead to the waste of computing and memory resource in the cluster.

BRIEF SUMMARY

Additional aspects and/or advantages will be set forth in part in thedescription which follows and, in part, will be apparent from thedescription, or may be learned by practice of the invention.

Embodiments of the present invention disclose a method, computer programproduct, and system for allocating memory. A computer receives a requestfor memory to be allocated to a computer node and determines if theallocation request needs to be carried out on a cluster level, a serverrack level, or on a server level. The computer retrieves a memory policyassociated with the determined level the allocation request needs to becarried out on from a memory policy database and determines how muchavailable memory may be allocated and if there enough available memoryto meet the request. The computer reallocates the available memory toaddress the received the received request based on the retrieved memorypolicy.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of certainexemplary embodiments of the present invention will be more apparentfrom the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment, in accordance with an embodiment of the presentinvention.

FIG. 2 is a functional block diagram illustrating a server rack, aserver level, and an individual server in the data processingenvironment, in accordance with an embodiment of the present invention.

FIG. 3 is a flowchart depicting operational steps of the memoryallocation within the data processing environment of FIG. 1, inaccordance with an embodiment of the present invention.

FIG. 4 is a flowchart depicting operational steps of the memoryallocation within the data processing environment of FIG. 1, inaccordance with an embodiment of the present invention.

FIG. 5 is a block diagram of components of a computing device of thedata processing system of FIG. 1, in accordance with embodiments of thepresent invention.

FIG. 6 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 7 depicts abstraction model layers according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The following description with reference to the accompanying drawings isprovided to assist in a comprehensive understanding of exemplaryembodiments of the invention as defined by the claims and theirequivalents. It includes various specific details to assist in thatunderstanding but these are to be regarded as merely exemplary.Accordingly, those of ordinary skill in the art will recognize thatvarious changes and modifications of the embodiments described hereincan be made without departing from the scope and spirit of theinvention. In addition, descriptions of well-known functions andconstructions may be omitted for clarity and conciseness.

The terms and words used in the following description and claims are notlimited to the bibliographical meanings, but, are merely used to enablea clear and consistent understanding of the invention. Accordingly, itshould be apparent to those skilled in the art that the followingdescription of exemplary embodiments of the present invention isprovided for illustration purpose only and not for the purpose oflimiting the invention as defined by the appended claims and theirequivalents.

It is to be understood that the singular forms “a,” “an,” and “the”include plural referents unless the context clearly dictates otherwise.Thus, for example, reference to “a component surface” includes referenceto one or more of such surfaces unless the context clearly dictatesotherwise.

Reference will now be made in detail to the embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings, wherein like reference numerals refer to like elementsthroughout. Embodiments of the invention are generally directed to asystem for allocating memory across multiple servers, a server rack,and/or on a cluster level. Using multiplexer (MUX) to create amemory-server topology and allow remapping of the topology of thememory, for example, memory expansion cards (MEC) to be connected tomultiple computer nodes, thus allowing the computer nodes to access theMEC.

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment 100, in accordance with an embodiment of thepresent invention. The distributed data process environment 100 includesa computing device 120, an administrator computing device 130, and aserver cluster 140 that are able to communicate with each other via anetwork 110. FIG. 2 is a functional block diagram illustrating a serverrack 1 150A, a server level 1 154A, and an individual server 160A in thedata processing environment, in accordance with an embodiment of thepresent invention.

Network 110 can be, for example, a local area network (LAN), a wide areanetwork (WAN) such as the Internet, or a combination of the two, and caninclude wired, wireless, or fiber optic connections. In general, network110 can be any combination of connections and protocols that willsupport communications between the computing device 120, server cluster140, and the administrator computing device 130, in accordance with oneor more embodiments of the invention.

The computing device 120 represents a computing device that includes anapplication 122 that may or may not have a user interface, for example,a graphical user interface. The application 122 may be any type ofapplication that is run on the a server contained within the servercluster 140, for example, the application can be a web application, agraphical application, an editing application or any other type ofapplication/program that requires access to a server on the servercluster 140 and the application 122 requires memory to run theapplication on the server side.

The computing device 120 may be any type of computing devices that arecapable of connecting to network 110, for example, a laptop computer,tablet computer, netbook computer, personal computer (PC), a desktopcomputer, a smart phone, or any programmable electronic devicesupporting the functionality required by one or more embodiments of theinvention. The user computing device 120 may include internal andexternal hardware components, as described in further detail below withrespect to FIG. 5. In other embodiments, the server cluster 140 mayoperate in a cloud computing environment, as described in further detailbelow with respect to FIGS. 6 and 7.

The administrator computing device 130 represents a computing devicethat includes a memory management module 132 that contains a userinterface, for example, a graphical user interface. The memorymanagement module 132 may be any type of application that allows a userto access a memory policy engine 144 and a memory policy databasecontained within server cluster management module 142, for example, theapplication can be a web application, a graphical application, anediting application or any other type of application/program that allowsto user to write new memory policy using the memory policy engine 144 orto manage the stored policy within the memory policy database 146.

The administrator computing device 130 may be any type of computingdevices that are capable of connecting to network 110, for example, alaptop computer, tablet computer, netbook computer, personal computer(PC), a desktop computer, a smart phone, or any programmable electronicdevice supporting the functionality required by one or more embodimentsof the invention. The administrator computing device 130 may includeinternal and external hardware components, as described in furtherdetail below with respect to FIG. 6. In other embodiments, the servercluster 140 may operate in a cloud computing environment, as describedin further detail below with respect to FIGS. 6 and 7.

The server cluster 140 is a server farm that contains a plurality ofserver racks 150A, 150B to server rack N 150C. Each of the server rackscontains a plurality of server levels 154A, 156A, to server level 158A,154B, 156B, and to server level 158B. Each of the server levels containa plurality of servers 160A, 162A, 164A, 160 b, 162 b, and 164 b. Eachof the server racks 150A, 150B, and 150C includes a server rackmanagement module 152A, and 152B. Most of the description will onlyreference server rack 1 150A and the components contained therein.However, the below description can be applied to every sever rack/serverlevel/server contained within the server cluster 140.

The server cluster 140 further includes a server cluster managementmodule 142. The sever cluster management module 142 includes a memorypolicy engine 144, a memory policy database 146, and possibly aplurality of multiplexers (MUX) 148. The server cluster managementmodule 142 controls the allocation of memory, for example, memoryexpansion cards (MECs) 180A, 182A, to 184A on a cluster wide level.

Each of the plurality of MUX 148 are a device that selects one ofseveral analog or digital input signals and forwards the selected inputinto a single line. Each of the plurality of MUX 148 can multiple inputsand/or multiple outputs to connected to the computer nodes 157A and 172Aand the memory, for example, the memory expansion cards (MECs) 180A,182A, to 184A. Multiplexers can also be used to implement Booleanfunctions of multiple variables, for example, the memory allocationpolicy rules stored in the memory policy database 146.

The memory policy engine 144 allows for an administrator to write,change, and/or delete memory policy allocation rules. The memory policyengine 144 further checks hardware limitations and user allocationconfiguration so that they can be converted to rules to stored in thememory policy database 146. The memory policy allocation rules can be,for example, based on; a) thresholds, for example, the minimum/maximumnumber of memory units can be assigned to each of the computer nodes157A, 172A, or the threshold rule could reference the timeout before oneof management modules 142, 152A, 170A and removed an allocated memoryunit from the computer nodes 157A or 172A for relocation; b) priority,for example, if one of the computer nodes 157A or 172A sends a requestfor more memory, while there is not enough and/or any available memoryfor reallocation, the rule determines in which sequence the memoryallocated to other computer nodes 157A or 172A should be reclaimed ifnot being utilized or should be forcibly removed from the computer nodes157A or 172A for reallocation; c) granularity, for example, allocatingthe memory to each of the computer nodes 157A or 172A based on theminimum hardware limitations of the memory and/or computer nodes 157A or172A. The above list of possible policy rules is not an all-encompassinglist of possible policy rules and it is not meant to be a limiting listof possible policy rules. The memory policy stored within the memorypolicy database 146, can be the same or different for each level ofallocation, i.e. cluster lever, rack level or server level.

Server rack 1 150A includes server level 1 154A, server level 2 156A, toserver level N 158, computer nodes 157A, server rack 1 management module152A, and a plurality of Multiplexers (MUX) 159A. The server rack 1management module 152A controls the allocation of memory, for example,memory expansion cards (MECs) 180A, 182A, to 184A on a server rack widelevel.

Each of the plurality of MUX 159A are a device that selects one ofseveral analog or digital input signals and forwards the selected inputinto a single line. Each of the plurality of MUX 148 can multiple inputsand/or multiple outputs to connected to the computer nodes 157A and 172Aand the memory, for example, the memory expansion cards (MECs) 180A,182A, to 184A. Multiplexers can also be used to implement Booleanfunctions of multiple variables, for example, the memory allocationpolicy rules stored in the memory policy database 146. MUX 159A and 148are disclosed on the cluster and rack level, but the disclosure is notmeant to be limited in any way. MUX 159A and 148 can be integrated atone location, combined in several locations, and/or maintained atseparate locations for the memory allocation.

Computer nodes 157 includes firmware and an operating system tocommunicate with the server rack 1 management module 152A and/or servercluster management module 142 to communicate about memory requests,memory failures and general memory status. The operating system of thecomputer nodes 157 is responsible for handling the memory hot add/removeevents, and sends acknowledgements, (partial) failure notifications tothe firmware of the computer nodes 157, and it should also be able todecide when to request more memory, or release memory upon request.Based on the demand for memory for an application that is running on theservers will determine the amount of memory requested by computer nodes157.

Server level 1 includes a plurality of individual servers 160A, a serverlevel 1 management module 170A, and computer nodes 172A. Server level 1management module 170A controls the allocation of memory, for example,memory expansion cards (MECs) 180A, 182A, to 184A on the server level 1154A.

Computer nodes 172A includes firmware and an operating system tocommunicate with the server level 1 management module 170A, server rack1 management module 152A, and/or server cluster management module 142 tocommunicate about memory requests, memory failures and general memorystatus. The operating system of the computer nodes 172A is responsiblefor handling the memory hot add/remove events, and sendsacknowledgements, (partial) failure notifications to the firmware of thecomputer nodes 172A, and it should also be able to decide when torequest more memory, or release memory upon request. Based on the demandfor memory for an application that is running on the servers willdetermine the amount of memory requested by computer nodes 172A.

One or more of the plurality servers S1 to SN 160A may contain at leastone or more memory expansion cards (MEC) 180A, 182A, to 184A. The MEC180A, 182A, to 184A can be assigned by the plurality of multiplexers 148and/or 159 to a computer nodes 172A and/or 157A per expansion card or byeven per a group of dual in-line memory modules (DIMMs) inside expansionunit.

FIG. 3 is a flowchart depicting operational steps of the memoryallocation within the data processing environment of FIG. 1, inaccordance with an embodiment of the present invention.

An administrator can determine if the memory needs to be reallocated andthe server cluster management module 142 determines if the memoryallocation requests to be carried out on a cluster, rack or level basedand refers the request to the appropriate management module (S310).Depending on what the determination is, i.e. if the memory allocation isto be cluster, rack or level, the management module 142, 152A, or 170Afor the respective allocation retrieves the memory policy from thememory policy database 146 (S320). The management module 142, 152A, or170A determines the current allocation of memory, for example, MEC 180A,182A, and 184A, as to which computer nodes 157A, 172A the memory isassigned or if the memory is currently unassigned (S330). The managementmodules 142, 152A, or 170A determines if there is enough unallocatedmemory to meet allocation request, and if not, the management modules142, 152A, or 170A determines if any of the current allocated memory canbe withdrawn from its current allocation (S340). The management module142, 152A, or 170A withdraw the selected memory from its currentallocation and/or determines if the memory has been released fromallocation (S340). The management modules 142, 152A, or 170A reallocatesthe memory based on the retrieved memory policy (S350).

FIG. 4 is a flowchart depicting operational steps of the memoryallocation within the data processing environment of FIG. 1, inaccordance with an embodiment of the present invention.

The server cluster management module 142 receives a request for morememory, wherein the request can be initiated by either an administratoror one of the applications that is running on one of the servers 160A,162A or 164A can automatically send out a request for more memory(S410). The management modules 142, 152A, or 170A determines if there isenough free or unallocated memory that be assigned to meet the memoryrequest (S415). If there is enough available memory, then the managementmodules 142, 152A, or 170A determines the memory allocation requests tobe carried out on a cluster, rack or level based and refers the requestto the appropriate management module (S420). Depending on what thedetermination is, i.e. if the memory allocation is to be cluster, rackor level, the management module 142, 152A, or 170A for the respectiveallocation retrieves the memory policy from the memory policy database146 (S425). The management modules 142, 152A, or 170A reallocates thememory based on the retrieved memory policy, for example, by assigningmemory to the one of the plurality of multiplexers 159A and thecomputers nodes 157A, 172A that is associated with the memory request(S430).

If there is not enough memory available, then the memory will needs tobe withdrawn from its current allocation to meet the memory request.Then the management modules 142, 152A, or 170A determines the memoryallocation requests to be carried out on a cluster, rack or level basedand refers the request to the appropriate management module (S435).Depending on what the determination is, i.e. if the memory allocation isto be cluster, rack or level, the management module 142, 152A, or 170Afor the respective allocation retrieves the memory policy from thememory policy database 146 (S440). The management modules 142, 152A, or170A determine how much memory is available and how much memory thatneeds to be withdrawn from its current allocation (S445). The managementmodules 142, 152A, or 170A determines what memory that can be withdrawnfrom its current allocation (S450) and withdraws the memory from itscurrent allocation (S455). The management modules 142, 152A, or 170Areallocates the available memory and the withdrawn memory based on theretrieved memory policy, for example, by assigning memory to the one ofthe plurality of multiplexers 159A and the computers nodes 157A, 172Athat is associated with the memory request (S460).

FIG. 5 depicts a block diagram of components of the administratorcomputing device 130 of the distributed data processing environment 100of FIG. 1, in accordance with an embodiment of the present invention. Itshould be appreciated that FIG. 5 provides only an illustration of oneimplementation and does not imply any limitations with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environment may be made.

Computing device 120, administrator computing device 130, server cluster140, server rack 150 a, server level 1 154A, and/or one of the serversof the plurality of servers 160A may include one or more processors 902,one or more computer-readable RAMs 904, one or more computer-readableROMs 906, one or more computer readable storage media 908, devicedrivers 912, read/write drive or interface 914, network adapter orinterface 916, all interconnected over a communications fabric 918. Thenetwork adapter 916 communicates with a network 930. Communicationsfabric 918 may be implemented with any architecture designed for passingdata and/or control information between processors (such asmicroprocessors, communications and network processors, etc.), systemmemory, peripheral devices, and any other hardware components within asystem.

One or more operating systems 910, and one or more application programs911, for example, server rack 1 management module 152A (FIG. 1), arestored on one or more of the computer readable storage media 908 forexecution by one or more of the processors 902 via one or more of therespective RAMs 904 (which typically include cache memory). In theillustrated embodiment, each of the computer readable storage media 908may be a magnetic disk storage device of an internal hard drive, CD-ROM,DVD, memory stick, magnetic tape, magnetic disk, optical disk, asemiconductor storage device such as RAM, ROM, EPROM, flash memory orany other computer-readable tangible storage device that can store acomputer program and digital information.

Computing device 120, administrator computing device 130, server cluster140, server rack 150 a, server level 1 154A, and/or one of the serversof the plurality of servers 160A may also include a R/W drive orinterface 914 to read from and write to one or more portable computerreadable storage media 926. Application programs 911 on computing device120, administrator computing device 130, server cluster 140, server rack150 a, server level 1 154A, and/or one of the servers of the pluralityof servers 160A may be stored on one or more of the portable computerreadable storage media 926, read via the respective R/W drive orinterface 914 and loaded into the respective computer readable storagemedia 908.

Computing device 120, administrator computing device 130, server cluster140, server rack 150 a, server level 1 154A, and/or one of the serversof the plurality of servers 160A may also include a network adapter orinterface 916, such as a Transmission Control Protocol (TCP)/InternetProtocol (IP) adapter card or wireless communication adapter (such as a4G wireless communication adapter using Orthogonal Frequency DivisionMultiple Access (OFDMA) technology). Application programs 911 oncomputing device 120, administrator computing device 130, server cluster140, server rack 150 a, server level 1 154A, and/or one of the serversof the plurality of servers 160A may be downloaded to the computingdevice from an external computer or external storage device via anetwork (for example, the Internet, a local area network or other widearea network or wireless network) and network adapter or interface 916.From the network adapter or interface 916, the programs may be loadedonto computer readable storage media 908. The network may comprisecopper wires, optical fibers, wireless transmission, routers, firewalls,switches, gateway computers and/or edge servers.

Computing device 120, administrator computing device 130, server cluster140, server rack 150 a, server level 1 154A, and/or one of the serversof the plurality of servers 160A may also include a display screen 920,a keyboard or keypad 922, and a computer mouse or touchpad 924. Devicedrivers 912 interface to display screen 920 for imaging, to keyboard orkeypad 922, to computer mouse or touchpad 924, and/or to display screen920 for pressure sensing of alphanumeric character entry and userselections. The device drivers 912, R/W drive or interface 914 andnetwork adapter or interface 916 may comprise hardware and software(stored on computer readable storage media 908 and/or ROM 906).

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 6, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 6 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 7, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 6) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 7 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and memory management module 96.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of thepresent invention. Therefore, the present invention has been disclosedby way of example and not limitation.

While the invention has been shown and described with reference tocertain exemplary embodiments thereof, it will be understood by thoseskilled in the art that various changes in form and details may be madetherein without departing from the spirit and scope of the presentinvention as defined by the appended claims and their equivalents.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the one or more embodiment, the practical application ortechnical improvement over technologies found in the marketplace, or toenable others of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method for allocating memory, the methodcomprising: receiving, by a computer, an allocation request for memoryallocation to a computer node; determining, by the computer, executionof the allocation request on a cluster level, a server rack level, or ona server level; retrieving, by the computer, a memory policy associatedwith the determined level for executing the allocation request, thememory policy being retrieved from a memory policy database;determining, by the computer, an amount of available memory forallocation and an amount of available memory; determining when there isenough of the available memory to meet the allocation request; andreallocating, by the computer, the available memory to an address of thereceived request based on the retrieved memory policy, when there isenough of the available memory to meet the allocation request.
 2. Themethod of claim 1, wherein the received request for memory was sent byan administrator to address a memory need.
 3. The method of claim 1,wherein the received request for memory was sent by the computer nodesbecause the computer node requires more memory to address the computernode's memory needs.
 4. The method of claim 1, further comprises: inresponse to determining that there is not enough available memory toaddress the memory request, determining, by the computer, what alreadyallocated memory can be withdrawn from its current allocation.
 5. Themethod of claim 4, further comprising: withdrawing, by the computer, theallocated memory from its current allocation in order to added theallocated memory to the amount available memory to meet the memoryrequest.
 6. The method of claim 1, wherein the memory policy memorypolicy associated with the cluster level, the rack level and the serverlevel are different.
 7. The method of claim 6, wherein an administratoris able draft and/or change the memory policies stored on the memorypolicy database.
 8. The method of claim 1, wherein the reallocating, bythe computer, the available memory to address the received the receivedrequest based on the retrieved memory policy, comprises: assigning, bythe computer, the available memory to the computer node associated withthe request and a multiplexer associated with the computer node.